Last 2 full weeks (Mon–Sun) · PostHog Production · timezone UTC ·
active = Application Became Active or app_opened ·
distinct users (person user_id, else person_id) ·
average of matching weekdays across both weeks ·
generated 2026-07-17
Recommended deploy window
Quietest single slot: Tuesday 02:00 UTC (~0 users avg).
Best 3-hour window on one weekday: Tuesday 00:00–03:00 UTC (~0.8 users avg).
Across all weekdays, safest deploy band: 22:00–02:00 UTC (~3.6 users avg) ≈ 01:00–05:00 MSK.
Quietest weekday overall: Tuesday (avg DAU 132.5). Busiest: Thursday (avg DAU 324.5) — Jul 9 spike pulls Thursday up.
Avoid peak hours around 11:00 UTC (~23.71 users avg across the week).
Tue 02:00
Quietest slot (~0 users avg)
22–02 UTC
Best band most days (≤~3.6 avg)
11:00 UTC
Busiest hour (~23.71 users avg)
Thu
Busiest weekday (avg DAU 324.5)
Weeks included
Week 1
2026-06-29 → 2026-07-05
Avg DAU120.9
Peak day06-29 (141)
Week 2
2026-07-06 → 2026-07-12
Avg DAU272.3
Peak day07-09 (518)
Daily active users
Mon
06-29
141
Week 1
Tue
06-30
112
Week 1
Wed
07-01
116
Week 1
Thu
07-02
131
Week 1
Fri
07-03
133
Week 1
Sat
07-04
101
Week 1
Sun
07-05
112
Week 1
Mon
07-06
130
Week 2
Tue
07-07
153
Week 2
Wed
07-08
190
Week 2
Thu
07-09
518
Week 2
Fri
07-10
405
Week 2
Sat
07-11
280
Week 2
Sun
07-12
230
Week 2
Note: Thursday 2026-07-09 DAU=518 is an outlier and raises Thursday averages.
Average active users by UTC hour (all weekdays)
Best deploy (≤5)Acceptable (≤12)Busy (≤22)Avoid (>22)
X: hour of day (UTC) · Y: average distinct active users across all 14 days
Heatmap — avg users by weekday × hour (UTC)
Best (≤5)Acceptable (≤12)Busy (≤22)Avoid (>22)
Each cell = average of that weekday×hour across the 2 weeks (e.g. both Tuesdays at 11:00). Hover a cell for the value.
Quietest & busiest slots
Quietest slots
Avg users
Fit
Tuesday 02:00
0
Best
Monday 01:00
1
Best
Tuesday 00:00
1
Best
Saturday 23:00
1
Best
Tuesday 01:00
1.5
Best
Monday 02:00
2
Best
Tuesday 03:00
2
Best
Wednesday 01:00
2
Best
Busiest slots
Avg users
Fit
Thursday 17:00
43.5
Avoid
Thursday 19:00
42
Avoid
Thursday 15:00
42
Avoid
Thursday 12:00
39
Avoid
Thursday 16:00
38.5
Avoid
Thursday 13:00
36
Avoid
Thursday 11:00
36
Avoid
Friday 09:00
35.5
Avoid
Hour × weekday detail (2-week average)
Hour (UTC)
Mon
Tue
Wed
Thu
Fri
Sat
Sun
Week avg
Deploy fit
00:00
2.5
1
3.5
2
4
4
2.5
2.79
Best deploy
01:00
1
1.5
2
5
5
5.5
2.5
3.21
Best deploy
02:00
2
0
3
3
8.5
3.5
3
3.29
Best deploy
03:00
2.5
2
5
6
11
5
8
5.64
Acceptable
04:00
6
10.5
11
8.5
22.5
10.5
7.5
10.93
Acceptable
05:00
6.5
7.5
12
10.5
26
8.5
12
11.86
Acceptable
06:00
15
8.5
15.5
13
33.5
15.5
20
17.29
Busy
07:00
13
12
19.5
24
34.5
24.5
20
21.07
Busy
08:00
20.5
14.5
20
30
25.5
14.5
21
20.86
Busy
09:00
10
14
20.5
24.5
35.5
16
23.5
20.57
Busy
10:00
16.5
18.5
16
32.5
22
19.5
26
21.57
Busy
11:00
19.5
16
19
36
26.5
28.5
20.5
23.71
Avoid
12:00
21.5
18
19.5
39
24
24.5
9
22.21
Avoid
13:00
13.5
14
19.5
36
33.5
22.5
17.5
22.36
Avoid
14:00
18.5
14
18
35
33.5
23
22.5
23.5
Avoid
15:00
9.5
11
19.5
42
23.5
21
18.5
20.71
Busy
16:00
12
11
15.5
38.5
20.5
20.5
22
20
Busy
17:00
13.5
8
14.5
43.5
32.5
24
16.5
21.79
Busy
18:00
6.5
10
17
34
27.5
15.5
20
18.64
Busy
19:00
15.5
18
16
42
16
18.5
14
20
Busy
20:00
6.5
8.5
10.5
27
15
12.5
13.5
13.36
Busy
21:00
7
12
7
15
11
4
6.5
8.93
Acceptable
22:00
4
5
3.5
11
4
4
3.5
5
Best deploy
23:00
3
5
2.5
5.5
3
1
3
3.29
Best deploy
Method: for each calendar day, count distinct active users per UTC hour, then average matching weekdays across
Week 1 (2026-06-29–07-05) and Week 2 (2026-07-06–07-12). Same identity rule as the weekend report.
Deploy fit bands are absolute thresholds on average concurrent users (not percentiles).